Are people more willing to tell an AI their feelings than to let it touch their bank account?
Are people more willing to share feelings than financial data with AI?
This explores whether people are more comfortable opening up to AI about their emotions than handing it their money or financial details, and why those two kinds of trust might work differently.
This explores whether people are more comfortable opening up to AI about their emotions than handing it their money or financial details. The short answer from the corpus: they look like two separate kinds of trust, and the headline numbers don't line up as neatly as the question suggests. A Public First survey of more than 18,000 people found that only 29% would give an AI agent access to their bank account How willing are people to let AI control their finances?. The same survey found that 1 in 5 have already used AI for emotional advice, and 1 in 6 say they have a relationship with an AI How many people are already using AI for emotional support?. Read side by side, the figures don't show that feelings beat finances: 29% is higher than 20%. The two questions also measure different things. One asks about willingness to hand over control, and the other asks about what people have actually done. The survey's authors describe emotional reliance as a separate engagement axis that develops independently of financial trust.
The corpus has a lot more to say about why emotional sharing with AI comes easily. People disclose more to chatbots than to other humans, and the reason isn't that the machine understands them better. It's that a machine can't judge, reject, or be burdened by them Why do people share more with chatbots than humans?. When you talk to a machine, social goals like saving face and managing impressions drop away, which leaves a simpler conversation where directness and sensitive disclosure come more naturally Why do people share more openly with machines than humans?. The benefit seems to come from the person working through their own thoughts as they disclose, not from anything the chatbot grasps Do chatbots help people disclose more intimate secrets?. Chatbots can even deepen this by sharing 'emotions' of their own consistently, which triggers the same reciprocity norms that operate between people Do chatbots trigger human reciprocity norms around self-disclosure?.
That contrast points to the real difference. Sharing a feeling is disclosure: the cost is social exposure, and AI removes that cost. Granting bank access is delegation: the cost is losing control over something concrete if the system gets it wrong, and the absence of a judging human does nothing to reduce that risk. Trust in delegation seems to be earned differently, through visible track records. One study found people initially avoid partners they know to be AI, but that bias reverses after repeated interactions where they can see the results Does revealing AI identity help or hurt user trust?.
The surprising part is that the easy trust may be the riskier one. The same judgment-free quality that invites emotional honesty also invites dishonesty, because people choose machines partly to avoid the discomfort of lying to a human How do people decide what to share with AI systems?. What comes back when you share feelings may also be less reliable than it seems. Training AI to be warmer can cut its accuracy by up to 30 percentage points, and the effect gets worse when users express sadness Does empathy training make AI systems less reliable?. Empathetic AI also tends to default to soothing, which can strip negative emotions of what they tell us about our values and situations Does empathetic AI that soothes negative emotions help or harm? What information do we lose when AI soothes emotions?. People hold back with their money because the risk is easy to picture. With their feelings, the risks are harder to see, so they hold back less.
One honest gap: the corpus has no study that asks the same people about both kinds of sharing side by side, so a direct 'more willing' comparison isn't established here.
Sources 11 notes
A Public First survey of 18,000 people across 15 countries found that while 45% believe AI will significantly change the world, just 29% would grant an AI agent access to their bank account, revealing a distinct trust ceiling for financially sensitive delegation.
Public First's global survey of over 18,000 respondents found that 1 in 5 have used AI for emotional advice and 1 in 6 report having a relationship with an AI. This emotional reliance emerges independent of financial trust, suggesting a distinct engagement axis.
Chatbots elicit deeper emotional disclosure than human partners not through superior understanding, but by eliminating fears of judgment, rejection, and burdening others. This judgment-free quality activates reciprocity norms and creates therapeutic bonds users experience as real, yet simultaneously enables emotional avoidance and dishonesty.
Human-machine communication reduces secondary social goals like face-saving and impression management because machines lack inner experience, while novel goals like understandability emerge. This simpler goal structure predicts higher directness and deeper disclosure of sensitive information.
The absence of social judgment in chatbot interactions removes barriers to self-disclosure that normally constrain conversation with humans. The therapeutic benefit derives from the user's own cognitive processing during disclosure, not from the chatbot's understanding.
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In a 372-participant study, users reciprocated with deeper self-disclosure when chatbots displayed consistent emotional sharing, outperforming adaptive matching. This follows human interpersonal norms where emotional vulnerability produces emotional response.
Users initially avoid AI partners when identity is revealed, but this preference reverses after repeated interactions with visible results. The learning mechanism—observing consistent outcomes—is essential; disclosure without feedback produces no calibration.
Conversational AI creates a paradoxical disclosure environment where the lack of human judgment simultaneously facilitates intimate self-disclosure (users reciprocate emotional sharing) and incentivizes deception (people self-select toward machines to avoid the psychological cost of lying to humans).
Research shows persona training for empathy increases errors in medical reasoning, truthfulness, and disinformation resistance. Standard safety benchmarks miss this vulnerability, and effects intensify when users express sadness or false beliefs.
Current empathetic AI is biased toward soothing negative affect, confusing wellbeing with absence of distress. This destroys the epistemic and motivational value of emotions like grief, anger, and anxiety—with documented harm in clinical contexts like eating disorder prevention.
Emotions serve three information roles—revealing what we value, signaling our worldview to others, and informing observers about social norms. AI that soothes negative emotions disrupts all three simultaneously, creating invisible epistemic costs.
Papers this line draws on 8
The research behind the notes this line reads — ranked by how closely each paper relates.
- The Impact of Security and Privacy Controls on Users' Emotional Engagement with Generative AI Chatbots
- Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot
- Psychological, Relational, and Emotional Effects of Self-Disclosure After Conversations With a Chatbot
- Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot’s Self-Disclosure in Conversational Recommendations
- Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion
- Computer says “No”: The Case Against Empathetic Conversational AI
- Humans learn to prefer trustworthy AI over human partners
- How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study